使用 Page rank problem.Mapreduce 错误时出错

Question

我一直在 Map Reduce 作业的帮助下研究 PageRank 算法。

我需要创建 Mapper 和 Reducer 类，我将借助它们创建 jar 文件。

我正在使用 jar 文件来处理 Hadoop 集群。

目前我的 java 个文件是 PageRank.java

import java.io.IOException;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import java.util.ArrayList;
import java.util.StringTokenizer;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;


public class PageRank {
    
    public class PageRankMapper extends Mapper<LongWritable, Text, Text, Text> 
    {
        public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException
        {

            String line = value.toString();
            line = line.replaceAll("\s+",";");
            StringTokenizer token = new StringTokenizer(line, ";");
            ArrayList<String> list = new ArrayList<String>();
            while (token.hasMoreTokens()) 
            {
                    list.add(token.nextToken());
            }
            int size = list.size();
            double ipr = Double.parseDouble(list.get(size-1)); //initial page rank
            String pageid = list.get(0); // pageid is always first element
            int numlinks = (size-2); // number of output links = size  - (first and last)
            double opr = ipr/(double)numlinks;  //output page rank = total/number of links
            String oprtext = (pageid + " " +String.valueOf(opr));
            int loop = 1;

            String outputlinks = "";

            while(loop <= numlinks)
            {

                   outputlinks += (list.get(loop)+" ");

                   context.write(new Text(list.get(loop)), new Text(oprtext));
                   loop++;
            }

            context.write(new Text(pageid), new Text(outputlinks));
        }
    }

    public class PageRankReducer extends Reducer<Text, Text, Text, Text>
    {

        public void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException
        {

                float fpr = 0.0f;
                String outlinks ="";

                for (Text value : values)
            {

                        String line = value.toString();

                        if (line.matches(".*\d.*"))
                {

                                String[] token = line.split(" ");
                                fpr += Float.parseFloat(token[1]);
                        } 
                else 
                {

                              outlinks += line;
                        }
                }

                String output = (outlinks +String.valueOf(fpr));
                context.write(key, new Text(output));

        }
    }        
    public static void main(String[] args) throws Exception {
                int i = 0;
                String opfile = "/part-r-00000";
                Path opath = new Path(opfile);
                Path inputPath = new Path(args[0]);
                Path outputPath = new Path(args[1] );
                while (i < 3)
        {

                        String suffix = ("/"+String.valueOf(i));
                        Path spath = new Path(suffix);
                        Job job = getNewJob(i);
                        i++;
                        job.setJarByClass(PageRank.class);
                        FileInputFormat.addInputPath(job, inputPath);
                        FileOutputFormat.setOutputPath(job, outputPath);
                        job.setMapperClass(PageRankMapper.class);
                        job.setReducerClass(PageRankReducer.class);
                        job.setOutputKeyClass(Text.class);
                        job.setOutputValueClass(Text.class);
                        inputPath = Path.mergePaths(outputPath,opath);
                        outputPath = Path.mergePaths(outputPath,spath);
                        job.waitForCompletion(true);
                }

        }
        private static Job getNewJob(int i) throws IOException 
    {
                Job job = new Job();
                job.setJobName("Page Rank "+ String.valueOf(i));
                return job;
 

   }

}

我的目录是什么样的

hduser@ajyj:~/pagerank$ ls -l
total 12
drwxr-xr-x 2 root root   4096 Oct 24 12:37 input_data
drwxr-xr-x 2 root root   4096 Oct 24 12:38 pagerank_classes
-rw-r--r-- 1 root hadoop 3824 Oct 24 13:39 PageRank.java

我已经创建了 hdfs 目录。

到目前为止，我正在按照一些教程进行配置。 https://www.youtube.com/watch?v=6sK3LDY7Pp4

我收到的错误是针对此命令的。

 hduser@ajyj:~/pagerank$ javac -classpath `hadoop classpath` -d '/home/hduser/pagerank/pagerank_classes' '/home/hduser/pagerank/PageRank.java'
/home/hduser/pagerank/PageRank.java:17: error: error while writing PageRank.PageRankMapper: /home/hduser/pagerank/pagerank_classes/PageRank$PageRankMapper.class (Permission denied)
    public class PageRankMapper extends Mapper<LongWritable, Text, Text, Text> 
           ^
Note: /home/hduser/pagerank/PageRank.java uses or overrides a deprecated API.
Note: Recompile with -Xlint:deprecation for details.
1 error

以上问题的任何解决方案....

Answer 1

此处，您有 permission denied 错误消息；

error while writing PageRank.PageRankMapper: 
/home/hduser/pagerank/pagerank_classes/PageRank$PageRankMapper.class (Permission denied)

目录pagerank_classes为root用户所有，只有root用户可以写入；

drwxr-xr-x 2 root root   4096 Oct 24 12:38 pagerank_classes

但是你是运行你的命令hduser。

我认为如果您递归地更改路径 /home/hduser/pagerank/pagerank_classes/PageRank$PageRankMapper.class 的文件权限（或所有者）以为当前用户提供写入权限，您的问题就会得到解决。

使用 Page rank problem.Mapreduce 错误时出错

Error while working with Page rank problem.Mapreduce error

java

hadoop

hbase

mapreduce